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Jefferies raises Tesla (TSLA) price target to $950 over strong demand, growing capacity

Stamping press at Gigafactory Texas. (Credit: Tesla)

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Tesla stock (NASDAQ:TSLA) recently received an optimistic outlook from Jefferies Equity Research, with analyst Philippe Houchois raising his price target on the automaker from $850 to $950 per share. Jefferies cited several reasons behind its update on TSLA stock, though the analyst noted that part of it is due to the growing gap between Tesla and legacy OEMs. 

“We raise EBIT estimates 7-9% for 2022-23 and PT to $950 on higher capacity ramp and sustained demand, following further analysis of Q3 data and various sources of information on the soon-to-be-launched Berlin facility. For some time, the narrative has been legacy OEMs closing the gap; we see little evidence as Tesla continues to challenge at multiple levels. We raise EBIT and margin estimates in contrast with doubts about earnings momentum across legacy OEMs,” Houchois wrote in a note

The Jefferies analyst noted that the demand has so far been stable for Tesla, and the company’s production capacity is getting better too. With strong demand and an ability to produce more of its products, Tesla could cater to substantially more consumers in the near future. Houchois estimated that even with a linear ramp, the addition of Giga Berlin and Giga Texas should add at least 500k units of actual capacity in one year. The analyst also noted that considering China’s recent results, concerns about domestic demand in the world’s largest EV market might be overblown

“We make minor changes to 2021 delivery estimates (910k), calculating production exit run-rate of 1.1m, and raise 2022-23 volume to 1.3-1.7m units. Modeling a linear ramp-up of production at the low end of guided 5-10k units/week for two similarly sized new facilities in Austin and Berlin, Tesla is set to add at least 500k units of actual capacity in one year to 1.6million and a solid 200-250k of actual units in 2022. 

“The final details of Q3 also showed China domestic sales of 73.6k units, putting to rest concerns about domestic demand, while annualized Q3 output yields 530k, i.e., Shanghai running at more than full capacity. Ytd Tesla delivered slightly more units than produced despite a still “immature” production network with cross-continent shipping accounting for c.20% of total production. Localizing production should improve delivery timing and associated transit costs,” Houchois wrote. 

Apart from these, the Jefferies analyst noted that based on the information it could gather from Giga Berlin, the plant seems to be heavily designed for simplicity. This should make it easier for the company to produce vehicles like the Made-in-Germany Model Y in a manner that is extremely cost-efficient and relatively simple. This, together with Tesla’s capability to weather the chip shortage crisis by adapting its products to what components are available, should allow the company to keep an edge against its peers. 

“From the information we could gather on the new Berlin facility, we noted that plant design was heavily flow-driven while the aluminum casting of both front and rear underbodies may reduce by c.40% the number of body-in-white components and robots required for welding and assembly. In a global auto industry plagued by complexity, Tesla continues to reduce complexity and set new standards for simplicity of design and assembly.

“Whilst Tesla has not been immune to supply disruptions in the course of 2021, it has outperformed peers in sourcing semi-conductors. From discussions with a senior expert in semi-conductor sourcing and manufacturing, we understand this partly reflects Tesla in-sourcing chip design with an ability to effect rapid re-design and secure more direct sourcing than peers,” the Jefferies analyst wrote. 

Disclaimer: I own TSLA stock. 

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Elon Musk

SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff

Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.

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Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.

The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.

Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.

Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.

The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.

Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.

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Investor's Corner

Tesla has one big financial question to answer for investors: Morgan Stanley

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Credit: Tesla

In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.

Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.

Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue

Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.

The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”

Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”

Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”

Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.

Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.

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Investor's Corner

SpaceX AI investment gamble will make it a big winner, firm says

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Credit: SpaceX

SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.

The firm also upgraded shares to a Buy from Hold and set a $160 price target.

SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.

Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.

There are plenty of ways the company can do this:

Leasing excess compute capacity through contracts

SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.

SpaceX is charging Anthropic massive money for its compute

High utilization driven by industry-wide scarcity

The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.

Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.

Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.

High incremental margins on the rental business once capacity is online

GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.

Parallel monetization of its own AI software and applications

Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.

These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.

Efficient, large-scale deployment and vertical integration advantages

SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.

Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.

SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.

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